data <- read.csv("data uas.csv", header = TRUE)

df <- data.frame(
  geo = c("IDN", "USA", "FRA", "CHN", "BRA"),
  Negara = c("Indonesia", "Amerika Serikat", "Perancis", "China", "Brazil"),
  Benua = c("Asia", "Amerika", "Eropa", "Asia", "Amerika Selatan"),
  Tahun = c(2020, 2020, 2020, 2020, 2020),
  Angka_Harapan_Hidup = c(71.5, 78.8, 82.5, 76.3, 74.0),
  Pendapatan_per_kapita = c(4000, 65000, 45000, 10000, 9500),
  Populasi = c(273000000, 331000000, 67000000, 1400000000, 212000000),
  Jumlah_anak = c(2.3, 1.8, 1.9, 1.6, 2.2)
)

library(ggplot2)

histogram_plot <- ggplot(df, aes(x = Angka_Harapan_Hidup)) +
  geom_histogram(binwidth = 2, fill = "skyblue", color = "black") +
  ggtitle("Distribusi Angka Harapan Hidup") +
  xlab("Angka Harapan Hidup") +
  ylab("Frekuensi")
print(histogram_plot)

bar_chart <- ggplot(df, aes(x = Negara, y = Pendapatan_per_kapita, fill = Benua)) +
  geom_bar(stat = "identity") +
  ggtitle("Pendapatan per Kapita per Negara") +
  xlab("Negara") +
  ylab("Pendapatan per Kapita")
print(bar_chart)

library(plotly)

library(dplyr)

scatter_3d <- df %>%
  plot_ly(
    x = ~Pendapatan_per_kapita,
    y = ~Angka_Harapan_Hidup,
    z = ~Populasi,
    type = "scatter3d",
    mode = "markers",
    marker = list(size = 5, color = ~Jumlah_anak, colorscale = "Viridis")
  ) %>%
  layout(title = "3D Scatter Plot: Pendapatan, Harapan Hidup, dan Populasi")

scatter_3d

interactive_plot <- ggplot(df, aes(x = Pendapatan_per_kapita, y = Angka_Harapan_Hidup, text = paste("Negara:", Negara))) +
  geom_point(aes(color = Benua, size = Populasi)) +
  ggtitle("Grafik Interaktif: Pendapatan per Kapita vs Angka Harapan Hidup")
ggplotly(interactive_plot)